人工噪音的效果如何?PHY安全场景的实时分析

Selahattin Gökceli, Özge Cepheli, S. T. Basaran, Günes Karabulut-Kurt, Guido Dartmann, G. Ascheid
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引用次数: 6

摘要

移动技术和设备的广泛使用带来了新的挑战,特别是在安全方面。在不久的将来,电池供电设备的数量也将显著增加。目前的安全方法不足以解决这些问题,高复杂度的加密技术也不适合此类设备。为了解决这些问题,最近出现了物理层(PHY)安全解决方案。一些5G候选技术,如全双工通信(FD)和人工噪声传输(AN),由于其性能优势,在各种PHY安全解决方案中得到了利用。本研究考虑一个类似工厂环境的场景,并利用FD和AN方法实时分析安全级别。本分析的目的是研究物理上安全的传输区域,并通过智能地使用AN扩展这些区域。我们提出的方法在一个由软件定义无线电(sdr)组成的测试平台上进行了实时评估。采用两种前端特性截然不同的设备作为窃听器,分析硬件对窃听性能的影响。实验表明,在窃听器上使用AN可以有效地创建鲁棒安全区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Effective is the Artificial Noise? Real-Time Analysis of a PHY Security Scenario
Expanding usage of mobile technologies and devices causes new challenges, especially in terms of security. In the near future, the number of battery powered devices will also significantly increase. Current security approaches are not sufficient for these issues and high-complexity cryptographic techniques are not suitable for such devices. To address these problems, physical layer (PHY) security solutions have recently emerged. Some 5G candidate techniques such as full-duplex communication (FD) and artificial noise transmission (AN) are exploited in various PHY security solutions due to their performance advantages. In this study, a scenario resembling a factory environment is considered and security level is analyzed in real-time by utilizing FD and AN methods. The aim of this analysis is to investigate physically secure transmission regions and to expand these regions by intelligently using AN. Our proposed approach is evaluated in real- time with a testbed that consists of software defined radios (SDRs). Two devices with very different front-end characteristics are utilized as eavesdroppers to analyze hardware effects on the eavesdropping performance. As observed with experiments, robust secure regions can be created by the use of AN on eavesdroppers effectively.
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